Scansion and Analysis of Prakrit Verses

8/12/2019 Scansion and Analysis of Prakrit Verses

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Extrait de la Revue Informatique et Statistique dans les Sciences humaines

XXIII, 1 4, 1987. C.I.P.L. - Universit de Lige - Tous droits rservs.

Revue Informatique Statistique dans les Sciences humainesXXIII, 1-4, 1987, pp . 99-110

Scansion and Analysisof prakrit verses

by text processing programsC.M. MAYRIIOFER

The use of computers in the study of metre has sevcral attractions aboyeaU the prospect of saving time and labour. There exist professional metricians,bu t for most students of language and literaturc metre in Hs technical aspectsis a rebarbatiye subject aU the more so far its dense and contradietorydocumentation. However, before one can use such deyices, one must be able tos ta te the rules of the metre in question. Now, even those who study literaturefor pleasure may be interested by the formalization of metrical rules, in so far asthe rules may be thought of as a model of the knowledge, the knowhow, whichin certain traditions of poetic composition is handed down from one generationto the next.European literary scholars who have studied metrics as a pradical scienceare likely to have absorbed t.he rules for scanning classical Greek and Latinverse. In several projeets t.hese rules have been adap ted to text-processingprograms and t.he results have appeared in a number of publications 1.

Unfortunately machines can make only an approximation of t.he scansionof a giyen line of verse, even if the approximation is right in as much as 95 2of cases. To improve this score their progl ammers would haye to foUow thepa th of reseal ch into automatic translation because the metrical propel tiesof a text in classical Greek or Lat in can he securely ascertained ouly artel it smeaning has been determined. In other words, the Greek and Latin alphabets

1 W. OTT, Melrische nalyse l zur rsPoetica des Horuz Goppingen, 1970; S. HOCKEYl\-IARRIOTT, Oxford Concordance Program version 1 0 : user s manual Oxford 1980,rcpr. 1984, pp. 334-337; discussion and bibliography in C. I UTLER Computers in LinguisticOxford 1985, p. 20.2 OTT, p. 7


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100 M MAYRHOFER

do no t sufficiently specify th e phonetic properties of their respective languagesta permit accurate metrical analysis on the basis of th e text alonc, whether byhumans or computers.

The case o f a no th er classical language \Vith a long tradition of metricalanalysis, Sanskri t, as ell as of its relations the Prakrits is very different.The devanagari alphabet in which these languages are usually writteu ha sabout twice as m an y c ha ra ct ers a s t he Roman. This multiplicity of charadershears witness ta th e precision of phonetic aoalysis in th e Indian grammaticaltradition. seems likell that a preoccupation \Vith the accuracl of orallyperformed ritual texts inspired th e development ofthis highll anall tic alphabetwhich has, thereforc, in principle, none of th e ambiguities of the Grcck an dRoman alphabets and t he fuies for scanning Sanskrit an d Prakrit verses ca nb e tra ns la te d into a text-processing program which will, again in principle,produce metrical analyses with 100 percent accuracy. Thi s h as been done, atleast for Prakrit 3.

The project to which l now turn concerns a particular Prakrit language.The Prakrits are regarded in the Indian tradition as th e heirs of Sanskrit,th e classical language par excellence. One of them, however, is qualified asapabhramsa, decadence being th e furthest rernoved from the parent language. is true that in sorne respects it is th e nearest to th e spoken languages of t hefamily. Nevertheless in th e evolution of literary styles in India it too becarne aclassicallanguage, an d a substantial number of text.s in Apabhramsa sorne ofthem very long, have been discovered an d published, almost all of them duringth e course of this centur y 4. Sti ll, it remains th e runt of th e family so far asscholarship is concerned. Th e tradition of linguistic an d metrical commentaryis less secure than in th e case of Sanskrit an d of th e o th er P ra kr its an dmodern scholarship ha s no t l et set tled th e rules of th e language. A generalproblern is that the editing of th e texts is no t sufficiently advanced t o p er mi t areliable sUl vey of its features, an d conversely, th e absence of an authoritativephonology and grammar means that th e editing of texts is hazardous. In orderto rnake progress i n e it he r direction, one must tr y to rnake progress in bothsimultaneously. The special interest o f m et re in Apabhramsa studies is thataIl known texts in th e language are metrical. There is no Apabhramsa prose.Consequentll one ha s the opportunitl to benefit from th e predictable featuresof verse to control th e accuracy of an exemplar of a text an d by th e saIlle tokenth e obligation to develop an adequate description of these features.

3 Dr. H. Nakatani of Tokyo University informed me in January 1985 thal he had th e useof such a program.

4 References n S. LIENHARD A ll story o Classical Poetry : Sans} ;ri PaliPrahit,Wiesbaden, 1984, index p. 290, S.v.


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SCANSION AND ANALYSIS OF PRAKRIT VERSES 1 1

The first step is the conversion of the texts into machine-reaclable form,which process takes the form of typing them in transliteration uncler a programwhich provides line-references in a standard format. For the transliterationwhieh involves rendering the 38 or so characters used in Apabhramsa by the26 of the Roman alphabet, certain deeisions had to be taken and adhered to.1 deeided to use the established system, in partieular the representation ofaspirate consonants by digraphs e.g. Kh ), except that instead of a variety ofdiacriticai marks (points above and below the letters, microns and macrons) 1use majuscules for most marked letters and random characters for one or two. Itwould have greatly simplified the programs described below if 1 had avoided thedigraphs, firstly because they constitute a peculiar set of characters, secondlybecause h in the usuaI system, and in mine, has an independent existenceas a let te r but to keep to convention seemed preferable mnemonically. Thebest system for this purpose is the one which causes the least hesitation in theoperator who is converting and typing simultaneousIy.Although such work ideally demands no refiection on the operator spart, it represents a significant s tage in metrical analysis because, despiteit s multiplieity of letters, the devanagari alphabet is not perfectly su ited toApabhramsa. Many of the letters are never used, except when an older Prakritor Sanskrit i tself is quoted sorne letters are used interchangeably; sorne sounclsare not represented by any standard letter. Two cletails will suffice to describethe significance of this for metrical analysis, but first sorne terms will have tobe defined. The metrical basis of Apabhramsa verse is quantitative, that is,the recurring elements of the system are classified by duration, no t stress orauy other linguistic feature. The fundamental element is the syllable, which 1shaH not attempt to define here except to note that its essential constituent isa vowel. For metrical purposes what matters is that a syllable may be eitherlong or l lshort . Vowels too are classifled as Ulong or shor t . Any syllablewhich contains a long vowel is long a syllable containing a short vowel may beshort or, i f a group of two consonants follows the vowel, long. Now, the vowelsin Sanskri t transcrihed as Ile and lO are regarded as diphthongs and hencehy clefinition long. In the Prakrit languages, however, there exist both long andshort e and 0 vowels. The majority of examples occur hefore a group oftwo consonants, indeed they are conditioned by that envronment 5. Hence theexistence of these short vowels is of no metrical significance. But they can occurin other contexts as weil, they can he metrically short, and the alphabet has

The so-called law of two morae : W. GEIGER Pali Literatur und Sprache Strasbourg,1961, p. 42. The rule that a short vowel becomes long if followed by a double consonantis enunciated by the Indian grammarian Hemacandra 1088-1172 AD)j see R. PISCHEL,r mm tik der Pral :ritSprachen Strasbourg, 1900, repr. Hildesheim, 1973, pp. 72-3.


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SCANSION AND ANALYSIS OF PRAKRIT VERSES 103

The purpose of this is to make it possible to examine a listing visually an dquickly pick up any irregularities. Though not l very fault in th e text will l l suitin an irregular scansion, it is almost certain that any irregularity in scansionwill be caused by a fault in th e text, introduced at sorne stage in th e copyingprocess from writer to p rinter to computer file. Flirther, since as we have seenthe transliterated text carries more information than the original, sorne errorswill be located in this information. Finally it is possible that the program mayno t he capable of correctly handl ing a particular cornbination of charaeters,though by now aIter rnany adjustments to eliminate banal inadequacies anynew failures will ad d significantly t o w ha t is known about th e language. Hence,once a text has been typed in transliteration, it is very useful t o p ri nt ou t thescansion of the file and have it by one s side while collating th e transliteration.

In Apabhramsa texts a particulaI metre may be used throughout a blackof verses, after which comes another block of a different metre, or a recurringstrophe-like arrangement composed of verses of different length may be used, orth e verses may be mixed. Espccially in th e last two cases it is useful to sort th efile of scanned verses by th e integer representing th e metrical length of eachline. This then produces blocks of related verses, which again ar e useful forvisual checks. The correctly-scanning neswill be grouped together by metre,an d any verses which contain a metrical fault that influences their length willfall outside th e black. Often there will occor between one black of regular linesan d th e next a well-defined group of stragglers that need editorial attention.

In such a listing th e eye will pick UP no t only irregularities, bu t alsoregularities. A particular metre is defined, no t only by its length in shortsyllable equivalents, but also in terms of perrnitted sequences of long an d shortsyllables. In a black of related lines the compulsory, preferred and forbiddensequences form visible patterns, an d by means of such an examination it ispossible to check the traditional rules an d to suspect further rules no t specifiedby th e tradition. There is n o d ou bt a circulari ty in using the rules of scansion tocorrect a text an d at th e same t ime using the text. to deduce rules of scansion,but such a prae tice is inherent in th e process of edi ting a text.

When finally th e whole file scans regularly, one can proceed ta use th escanned file, t he o ut pu t of th e first s tage, as input for a further stage, that ofsubmitting th e traditional rules an d one s own intuitions concerning t he natureof a given m et re t o a rigorous analysis. The re a re two fundamental approachesto metrical analysis at this level, sometimes qualified as outer an d innermetrics : bath study permitted sequences of long and short syllables, but th eformer concentrates on th e verse and its articulations, t he l at te r concentrateson the word in relation to th e verse and its articulations. Thus for example inth e Greek and Latin hexameter, th e verse must begin with a long syllable -);


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104 C.M. MAYRHOFERthat advances the count of short-syllable equivalents ta 2; the count may thenjump ta 4 with another long syllable - -), or it may increase fust ta 3 _ then ta 4 - with short syllables, bu t it must then advance from 4 ta 6 :- - - or - y v _ the count can never he 5. Then follows one long syllable or twoshort and sa on , ta the line limit of 24. The regtar increment in the Hoe of 4short-syllable equivalents, consisting of one long syllable followed by a long ortwo shorts, constitutes a foot. Indian paeties also uses the ward equivalent ta {oot H but in a different sense. The ward gana is used with reference ta Prakritverse for a concept somewhat like that of the foot, except that no t every nin a verse has the same valuc, that the formula of a verse might b e l nsteadof for example 6 4 as in the Greek and Latin hexameter, something likc6+4+3+6+4+1 , and the specifications for a particular gana can range fromonly this sequence of long and short syllables is allowed ta l any combinationof long and short syllables is allowed provided that the total of the short-syllableequivalents is n 7.

The program which deals with t he ou te r metric1J of Apabhramsa versebegins by collecting certain data interactively from the terminal : the nameof the metre (for the heading), the number of gana in a verse, the number ofshort-syllable equivalents in each gana. The SUffi of these is used to select versesin the file for closer attention j the program then asks the user to prescribe twofeatures of the verse in the form of two columns of the scanned file e.g. incolumn 21 and column 25 the charader l U must appear) so that differentmetres of the same length can be distinguished. After the data are elicited, theprogram reads the scansion file Hne by Hne, checks each Hne for it s metricallength, and if the length is that of the verses under investigation, applies thecolumn-matching test. the liue passes the test , the program splits i t into ganasas prescribed. Each gana is matched against an array in which are accumulatedthe gana-types found during the current run, and a two-dimensioned integerarray keeps count of the occurrences of each type in each place of the verse. Theresults are tabulated with the actually-occuring gana-types sorted by length,along one axis and a heading identifying the gana by it s place in the line alongthe other j the intersections give the number of times that the gana takes aparticular form at a particular place. See table 1 for an example of the outputof this program j the verses analysed are from the 8th chapter of SiricandaKahako3a.

7 For a view of the basis and development of gana metres, see E.I


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SC NSION ND ANALYSIS OF PR KRIT VERSES 5

T LE N TYPESNumber of doha read in scande 40G Nul 4u u Ul 25u lu Ul 3U U U 2u Ul__ l 6 u lu _ 2 5__ U U

7 7 __ lU u 3 U u __ 4 2u UIU Ul U U U U 33 U U u u l

u UIU u 3U __ U u u lu u __ UU luU l u u u Ul__ u Ul u Ul____ 2U u __ lu Ul uuuluuUu UI__I_ __ UIU __ 2 __ u u __ 2 U U ____

2 __ UIUlu u __ u Ul_ 4 6UU l u u uU I UU l u uUU ____ u u 3 __ u U I __ u __ Ul _U Ul 3 2

lU U U U 2uuuuluul u u lu u l__ 3__ u u l u u l u u ____ 1 __ ulul_ ____ u ul uuuuluu UUUIU __ 2 u u u __ u __ U __ u

Innee metrc can not he entirely separated from


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106 C.hL MAYRHOFERthe permitted sequence of long and short syllables in a verse determines theshapes of words that are admissible in that verse at particular places in theverse. But Hinnee metric is alsa concerned with ta put it one way, the metricallength of words occurring in a verse, to put it another \Vay \Vith the places ina verse where one word may end and another begin. Concerning the former,there are regularities ta he discovered in the favoured word-shapcs of a givenlength, bath absolutely and in relation \Vith their place in the verse; traditionalmetrics has nothing ta say about these. Concerning the latter traditionalmetrics prescribes places in the verse where there i s a lwa ys a w or d- di vi si on ,but is reticent about the places where there i s n ev er a wo rd- di vi si on . This isno t the place to give details of the phenomena to bc investigated; the methodof the program which tabulates them is, briefly : for a line of given metricallength which passes the colunm-content tes t as abovc, read the metrical shapesbetween word-divisions and store them in a text anay of which each gradecontains one type with a count being kept in a two-dimensioned integer arrayof the occurrences of each type in a particular place. The resul ts are thentabulated with the actually occurring ward types sOl ted by length along oneaxis, and along the other axis a heading which divides the ne into columusnumbered to represent the place in the verse, 50 as to locate the places wherethe words begin the intersections give the number of times that a word of aparticular shape begins at a particular p la ce i n the line. Ta facilitate the stndyof the general metrical nature of the text the SUlU of aU the occurrences of aword of a particulaI shape is given at the end of a row. One cau then see at aglance if, for example anapaestic words are favoured over dactylic, or whatever.Ta facilitate the s tudy of the obligatory and fOl bidden ward-divisions, the lastrow gives the sum of eaeh column. Table 2 gives an example of the output ofthis program using the same material as in table

The aim of these programs is essential1y to reconstruct the criteria ofcorrectness in the various metres of Apabhramsa verse, or to verify the criteriain cases where t hey are provided by traditional eommentaries or have alreadybeen estabHshed by modern scholarship. seems entirely appropriate to use acomputer ta perform quickly and accurately the inherently disagreeable tasksof gathering and sorting the data as a means to the end of deducing the rulesby which the poets worked, sa ta spe ak . 1 p ass over the problem of the statnsof these rules. There is probably no way of deciding whether the regularitiesw hi ch e me rg e f ro m this presentation of the data arise from the system of thelanguage itself or from the craft of the poet working within a tradition; mostcases would no doubt involve a mixture of the two in varying proportions. lhave resisted the temptation to explore the regularities for themselves beyondthe point where the may intuitively be associated with or considered as modelsfor the practice of the poets. But that there are perspectives in the formai basis


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SC NSION ND ANALYSIS OF PR KRIT VERSES

TABLE 2 : W OR D TYPESNumber of 24 morae lines read in scande 40LiST OF WORD TYPES

107

1 :2:3 :5 :6:7:8:9:

1 :11:12 :37 :38 :39 :40 : :42 :43 :44 :

uu uu u u UU U UUU U U U U U_ _ uuu U_ _ _ _ _ _ u u uU U U U U U U U U U U U U U U UU U U U U U U U U U U U U U U U

of versification beyond this point is constantly impressed on one. To take oneexample : in a rhyming couplet in the p h ik metre there are 32 shortsyllable equivalents and an obligatory word break for the rhyme at the mid-point. Hence the longest possible word contains 16 short syllable equivalentsand words of this length lli e not uncommon. this poetic language there is nosimple inverse relationship hetween word length and frequency. The number ofpossible shapes of words hetween 1 and 16 short syBable equivalents is about4000. Sorne of these are excluded by the metre but probably the metre beingvery accomodating less than half : say then that the number of possible shapesis 2000. In praetice about 100 seems ta he the maximum and it is a practicalmatter for the programmer because influences the dimensioning of the arrays.To explain why relatively few of t he possible word shapes are used one wouldprobably have to invoke the formai properties of the language itself.

A further use for a file of scanned verses is the study of rhyme. As hap-pens not ouly are aIl known Apabhramsa texts in verse but also nearly aIl


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the verses are rhymed. Traditional pocties recognizes rhyme or rather rhymelike phenomena as a repetition of sounds at the end of \Vords or homonymous\Vords at the verse end. This leaves l oom for further investigation in terms ofthe lexical choice, morphology and metrical shape of rhyming clements. To begin with, i t is necessary ta define rhyme, as understood in European poctiesin terms of metre. Words with similar cudings are ouly rhymes if they Dccur ata determined place in a verse: typically, the end of the verse, but that faisesthe question of the relationship between the verse and the lines as presentedon the page. For example the verse referred to above can he printed as

1 1617 32

or as1 32In the former case, each Jiue will end with a rhyming word; in the latter,

there will be a compulsory word-break after the 16th place, and the word wruehends there will rhyme with the word at the end of the line. A more eomplicatedexample is shown in the figure below, in which the numbers l epresent the placein the verse, the letters represent the words which rhyme \Vith one another inthe same or in successive lines :

1 lO a 18 a 31 b1 lO e 18 e 31 b would undoubtedly have simplified the programming if the verses were

typed so that rhymes occurred only at the end of lines, but for the sake of easein collation and cross-reference the lines represent the versesas they are usuallyprinted. So the program must n.nd the places in the verse where a rhyming wordi to be expeeted, and extraet that word. This is done y reading the text fileand the scanned file concurrently the latter being derived from the former,corresponds with it line by Hne and counting in any particular Hue startingat the end of the Hne the number of w o r ~ v s o n markers that occur in thescaIUled text before the prescribed metrieal place is reached this is of course1 in the most frequent and trivial case, end-rhymes ; then extracting the wardfrom the text which occurs after the same number of word-divisions, againcounting from the right. The same process is repeated as necessary in arder taextraet the other member of the rhyming pair, and once that has been done,


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SCANSION AND ANALYSIS OF PRAKRIT VERSES 109

the elements that are common to the ends of both words are extraeted. This issimple enough when both occur on the same line a l it tle more delicate whenthey OCCUl on different lines and qui te awkward when there is a mixture ofthe two schemes as in the example above. In praetice 1 have a procedure forthe case of rhymes in the same line and another for the case of rhymes in adifferent n and 1 simply rewri te a sect ion of th e prograrn to cope with eachparticular job. would be more elegant bu t very time- consuming to writea prograrn that could accommodate every pattern. When the rhyming wordshave been extracted, the program sends to a file a record consisting of theelements cornmon to the endings of the two words - in other \Vords the rhyme- reversed for sorting purposes and the two words involved together with then reference of one of them.

Of these higher-Ievel programs the least useful in the sense of givingnew insights is the most obvious that which classifies gana Scholars havecollected this kind of material before and it is at least reassuring to findthat the results produced by my program correspond with those producedmanualiy by others. such statistics are needed again they may be entrustedto a machine. The rhyme program was written and applied in the hope ofconfirrning a hypothesis that, not evcry allowable and actually-occurring wordending is used in rhyme but that a relatively smali group of rhyming elementsis used relatively frequently. It did not fulfil trus hope. There are matters tobe discovered about the choice of rhyrning words but the phenornenon is notsimply lexical or morphologieal as was first thought. On the other hand thesorted output of rhyming words revealed at the head of the list an unexpectedgroup of blanks where the words in rhyming position did not end with commonclements. More preeisely the common elements were of a kind that the programwas no t written to deteet. Such rhymes are of considerable interest for the studynot only of the poetics but also of the phonemics of the language: it appearsthat the poetic rules deem certain non-identicalletters to correspond with oneanother and certain non-nun letters to he nul . These rules are of course notdirect evidence for the phonemics of the language but they clearly need tobe taken into account under that heading 8 The rhymes can perfeetly weIl hecollected manually. However when one is not sure at the outset what one islooking for it is aIl advantage to be able to repeat the process of collectionwith different criteria in negligible time and this can be done by means ofminor modifications to the program.

8 For discussions of impure rhymes see H. JACOBI, Bhavatta Kaha von Dhanavala :eine Jaina Legende in Apabhromsa Munich, 1918 pp . 52-3; G. B UM NN Drei Jainagedichtein ltGujarati Wiesbaden) 1975 pp. 1921.


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XXIII 1 4 1987 C I P L U i it d Li T d it

11 C M MAYRHOFER

The most useful program is without doubt the one which classifies wordtypes. Not ouly does it yield interesting information on the structure of theverses which are submiUed ta it but it also provides a table of the frequencyof occurrence of caeh metrical shape of the words in a text. Inasmuch as metrieal shape is considered to be a factor in the historieal morphology of theludo Aryan languages 9 this material has an importance beyond the study ofpoetic practices and in a subsequent project this funetion of the program willbe applied ta the automatic construction of word lists arranged by metricalshape from the texts uncler consideration.

T LE OF DISTRI UTION OF WORDTYPESY ST RTING POINT

1 3 5 7 9 11 13 5 7 19 3 5 7 9 31 33 35 37 39 41 SUM1 o o 3 1 1 52 8 2 3 2 1 3 o 5 2 3 53 6 3 1 4 5 24 3 o 3 2 2 2 1 135 4 1 4 3 9 276 o o 1 1 1 o 15 87 5 4 4 6 28 1 o 19 1 o 1 1 2 1 6

1 o o 1 1 o o o 1 112 o 1 2 5 837 o o 1 138 o o 1 139 o o 1 14 o o 1 14 1 o 142 o 1 143 1 o 144 1 o 1

SUM 4 4 7 15 1 3 2 2 3 o 38 o 16 5 17 15

9 O. V HINBER as iiltere ittelindis h im berblick Vienna 1986 90

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Scansion and Analysis of Prakrit Verses